Calendar of Events
Implicit Bias: Racial Gaps and Scientific Gaps
Speaker: Lee Jussim, Rutgers University - Psychology
Abstract: I critically evaluate the concept of implicit bias and its most common measure, the Implicit Association Test, with the goal of better understanding how much it can explain real world racial gaps. This is especially difficult to do because the many conceptual, methodological, and validity controversies related to the IAT undercut the ability to reach conclusions about implicit bias with much confidence. The IAT not a clean measure of either implicit biases or of associations. Nonetheless, several meta-analyses have shown that IAT scores predict discrimination to at least a modest extent. To address its ability to account for racial gaps, I work backward. Given the size of some gap, how much of that is likely to be explained by IAT scores? Although I do not answer the question quantitatively, I present a series of heuristic models intended to provide increased clarity about the likely range of possibilities. Alternative explanations for gaps are briefly reviewed, and our models make clear that IAT scores can only explain what is left over, which is likely to be only a modest portion of those gaps. I conclude by summarizing the pessimistic findings from a recent review of prejudice and implicit bias reduction trainings.
Host: John Paul Chou